基于PCA和SOM模型的龙感湖水质时空动态研究

SPATIO-TEMPORAL DYNAMICS OF WATER QUALITY IN LONGGAN LAKE BASED ON PRINCIPLE COMPONENT ANALYSIS(PCA)AND SELFORGANIZING MAPPING NEURAL NETWORK(SOM)MODELLING

为评估湖泊渔业模式转型阶段水环境的时空动态,选择长江中下游典型湖泊龙感湖为研究地点,于2017—2018年对该湖的黄梅水域和宿松水域进行周年季度水质监测,通过主成分分析(PCA)和自组织特征映射人工神经网络(SOM)模型定量分析了水体理化参数的时空变化特征,采用综合营养状态指数法(TLI)对水体富营养化状况进行了评价。PCA分析结果表明,龙感湖宿松水域和黄梅水域的水质差异较小,季节动态明显。全湖氨氮夏季平均浓度高达0.64 mg/L;总氮夏季平均浓度为2.30 mg/L,冬季平均浓度为1.04 mg/L;叶绿素a夏季平均含量达95.28μg/L,秋季平均浓度为28.30μg/L;pH夏季最高,达9.27;总磷冬季最高,平均为0.22 mg/L;TLI指数表明龙感湖除秋季属于轻度富营养水体外,其他3个季节均属于中度富营养状态。SOM模型结果具有可视化强的优点,能够更清晰和直观地反映龙感湖水质的时空分布动态。围栏拆除和禁渔等管理措施有助于湖泊渔业环境修复和资源恢复,建议对渔业模式转型后的湖泊生态系统变化进行长期跟踪监测评估。

In order to evaluate the spatiotemporal dynamics of water quality during the transformation stage of lake fishery model,we selected Longgan Lake,a typical lake in the middle and lower reaches of the Yangtze River,as our research site.From 2017 to 2018,seasonal water quality monitoring were conducted on the Huangmei waters and Susong waters of the lake.Principle component analysis(PCA)and self-organizing mapping neural network(SOM)modelling were used to analyze the spatiotemporal changes of physical and chemical parameters of water body.The eutrophication status of water body was evaluated by the method of comprehensive trophic level index(TLI).PCA results indicated that the water quality of Susong and Huangmei waters in Longgan Lake had little difference,while the seasonal dynamic was obvious.The average concentration of ammonia nitrogen in the whole lake was the highest(0.64 mg/L)in summer.The average concentrations of total nitrogen in summer and in winter were 2.30 mg/L and 1.04 mg/L respectively.The average concentrations of chlorophyll a in summer and autumn were 95.28μg/L and 28.30μg/L respectively.The pH value was the highest(9.27)in summer,while the average concentration of total phosphorus was highest in winter with the value of 0.22 mg/L.The TLI index showed that Longgan Lake had a mild eutrophic level in autumn and a moderate eutrophic state in the other three seasons.The results of SOM model clearly and intuitively reflected the temporal and spatial distribution of water quality in Longgan Lake.Management measures such as eliminating purse seine and prohibiting fishing can help restore lake fishery environment and fishery resources.It is suggested that a long-term follow-up investigation and assessment should be carried out on the lake ecosystem after the transformation of fishery model.